{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from mpl_toolkits.axisartist.axislines import SubplotZero"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0,1,1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = -2 * x*x + 2*x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1, (10, 6))\n",
    "ax = SubplotZero(fig, 1, 1, 1)\n",
    "fig.add_subplot(ax)\n",
    "ax.axis[\"xzero\"].set_visible(True)\n",
    "ax.axis[\"xzero\"].label.set_color('green')\n",
    "\n",
    "ax.axis[\"x05\"] = ax.new_floating_axis(nth_coord=0, value=0.5,axis_direction=\"bottom\")\n",
    "ax.axis[\"x05\"].toggle(all=True)\n",
    "\n",
    "ax.grid(True, linestyle='-.')\n",
    "ax.axis[\"top\",'right','left','bottom'].set_visible(False)\n",
    "plt.plot(x,y,color=\"red\")\n",
    "plt.plot((0.5,0.5),(-0.1,0.55),color=\"green\")\n",
    "plt.text(0.51,0.56,\"p = 0.5\",fontdict={\"fontsize\":14})\n",
    "pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
